Journal of Urban Planning and Development

Knowledge of the real-time behavior of a city would encourage making decisions in urban design in a dynamic way, adapting to what the city constantly needs, without further large periodic studies. This paper proposes a system for gathering heterogeneous real-time traffic data coming from several sources of information and making decisions in urban design in a dynamic way. This innovative tool, based on new Information and Communications Technologies (ICTs), allows an iterative design, surpassing classical urban planning. This methodology evaluates, diagnoses, and redesigns street sections with the aim of achieving an optimized mobility system. In case of cities without an urban mobility plan, the tool will assess the adequacy of the current street design. In cities with an urban mobility plan, the system becomes an effective tool to verify the guidelines of the plan before being applied. A prototype has been tested in Málaga, Spain, showing the feasibility and usefulness of the tool.

The performance of transport systems is seldom considered when designing land-use development planning, which could result in a deteriorated transport system. One of the major goals of a transport system is to improve individuals’ accessibility or the ease of reaching desired activities, destinations, and services. For urban smart growth, policymakers usually face a challenge of how to coordinate land-use development in multiple urban centers in order to optimize accessibility. This paper aims to provide an optimal land-use development method in terms of system accessibility. A novel bilevel model system is proposed to represent the problem where the upper level aims to optimize transport system performance in terms of accessibility, and the lower level is a four-step model with feedback to achieve transport system equilibrium. A multinomial logit model is used for destination choice, which can adequately capture traveler decision behaviors compared with the gravity-analogous model. To find the optimal solution of the proposed bilevel model, an efficient algorithm is proposed on the basis of a Dirichlet distribution, method of successive averages (MSA), Frank-Wolfe algorithm, and Dijkstra algorithm. An experimental study using the Nguyen-Dupuis network is presented to verify the effectiveness of the proposed model and solution algorithm. The research demonstrates that the optimal control of land-use development is critical to network accessibility, and the modeling framework can be a useful tool in determining urban development policies.

In recent years, China’s air pollution has drawn worldwide attention and has become a challenge for the Chinese government. Air pollution adversely impacts not only human health, but also property values. Employing the air pollution and housing price data covering 282 prefecture-level cities in China, this article confirms that air pollution has been negatively capitalized into cross-city housing prices. In addition, this article applies the local geographically weighted regression (GWR) model to unveil the spatial variation of air pollution’s capitalization effects on housing prices across different cities. Because air pollution will negatively impact housing prices, considering the benefits of air quality can help the government to create public policies intended to address air pollution, as well as help the public to improve both awareness regarding the environment and willingness to pay for improved air quality. Combing ordinary least squares (OLS) and GWR, this research serves to improve our understanding of air pollution’s capitalization effects on housing prices across Chinese cities.

Public spaces have long defined the structure of cities and articulated the different private spaces where urban life unfolds. Over the past decades, profound asymmetries have emerged from the evolving social, economic, and spatial structures within urban areas. The growing role of private authorities in urban development and management has created new arenas for public life, changing the role of public spaces and the way society interacts with the city and the broader public sphere. Instead of attempting to understand public space through a specific thematic lens, the concept of publicness can explain the complex intricacies that justify its public nature, essential to clarifying this contemporary positioning. To properly address the current challenges of the public–private urban paradigm, the concept of publicness needs to combine distinct physical features, operation schemes, and management profiles. This paper presents a novel approach toward the use of publicness as the foundation for a space evaluation model, creating a tool to successfully integrate both new and existing spaces in the contemporary urban realm.

The spatial correlation between urban sprawl and the underlying road network has long been recognized in urban studies. Accessibility to road networks is often considered an approximation for the measurement of human mobility, which is a key factor in determining potential urban sprawl in the future. Despite the close relationship between urban development and road networks, the spatial dependency of these two spatial layers has never been systematically evaluated. This study conducted a comprehensive investigation on the spatial dependency between these two spatial layers using an urban expansion data set between 2000 and 2010 of East Asian regions and the road network data from OpenStreetMap. Four Chinese cities, namely Beijing, Shanghai, Chengdu, and Shenzhen, were selected to conduct the analysis. The spatial correlations between the urban sprawl and road networks were first quantitatively analyzed using Ripley’s cross-$K$ function. Highly significant spatial correlation has been observed in all four tested cities. A Bayesian network model was also developed to verify the predictability of urban sprawl using the spatial and structural features extracted from the existing road networks as well as the spatial pattern of the past built-up areas. The results show an affirmative answer to the predictability of urban sprawl by achieving an overall accuracy of 79% in classifying urban sprawl and undeveloped areas. Finally, the hidden dependencies among the urban sprawl and the extracted spatial features were interpreted and analyzed based on the Bayesian network structure learned from the data.

Successful development of new towns is vital for a healthy, highly efficient, sustainable, and symbiotic metropolis. By quantitatively comparing the spatial characteristics and evolution processes between mother city and new towns using a multinomial logit (MNL)–based cellular automata (CA) land-use change model, this study aims to find solutions for new town development predicaments, e.g., failure to attract businesses and lack of urban living and prosperity. Wuhan metropolis, China, constituted by the existing mother city and six new towns, is used for the case study. At a cell level ($50\times 50\mathrm{m}$), land-use data from the Wuhan metropolis in years 2000 and 2010 are used for model calibration. For both the mother city and the southeastern new town, the calibrated parameters of MNL models are analyzed to explore the roles of various spatial characteristics on land-use development. Furthermore, analysis of the model shows that it can capture the real regulations of spatial growth for both mother city and new towns. Scenario analysis concludes that the interactions between mother city and new towns are the critical factor for a successful spatial growth simulation. To successfully create similarly vital and lively urban life as that in the mother city, new towns should focus comprehensive development on diverse neighborhoods and improve the attractiveness of the local center. From the perspective of characteristics of spatial evolution, this study reveals the reasons why some new towns fail to create a vital and lively urban life, which is helpful for better development of new towns.

Urban greenspaces play a key role in mitigating the urban heat-island (UHI) effect. The aim of this study is to quantify the effects of area and shape of a greenspace on urban cooling using correlation analyses and regression models. This was achieved by taking a very densely populated urban area in Nanjing, China, as a case study and classifying 78 greenspaces within the study area into nine groups based on size and shape. Cooling distance and intensity values were calculated based on the land surface temperature derived using remote sensing. The results indicate that (1) large and regular greenspaces have a greater cooling distance than small and irregular ones; (2) in general, an increase of area can enhance the cooling intensity of a greenspace when it is smaller than a certain threshold (i.e., 10 ha); and (3) reducing the shape complexity of a greenspace can enhance cooling intensity when greenspaces are larger than 5 ha. This study provides insights for urban planners and landscape designers to determine better combinations of area and shape of urban greenspace in order to effectively alleviate the UHI effect.

This paper aims to investigate the implications of land use/cover (LUC) changes on local climates in Sabang City from the year 2000 to the year 2015. In the years 2000 and 2015, LUC maps were derived from remote-sensing satellite images using a supervised classification method (maximum likelihood). Both 2000 and 2015 LUC maps contained four categories: built-up area, forest, cropland, and wetland. The 2000 LUC map had a kappa coefficient ($K$) of 0.72, while the 2015 LUC map had a kappa coefficient of 0.76. Climate changes were determined in four variables: air temperature, rainfall, humidity, and wind velocity. The results demonstrated an immense LUC change within the span of 15 years. Forest areas dropped to nearly 45%. Built-up areas expanded by nearly 85%. For the most part, forest areas were converted into cropland. On the other hand, temperatures rose while humidity declined. Rainfall and wind velocity were in a relatively stagnant state within this 15-year period (2000–2015).

Most of the urban sustainability studies consider a city as a single entity to evaluate their sustainability performance. Indian cities are heterogeneous and a collage of many diverse entities that have a variety of built characteristics, termed as spatial clusters in this paper. The study presented in this paper aims at assessing sustainability of an Indian city at an appropriate microscale of clusters, a basic spatial unit, wherein the evaluation can be used as a diagnostic tool for improving sustainability. It identifies indicators within various sustainability domains and uses an indicator-based assessment method. Identification and categorization of various cluster typologies is done on the basis of morphology, development patterns, location, and occupants’ income range in Nagpur. Based on household survey data, performance of each cluster and cluster typology is compared, which helps in identifying and prioritizing issues and clusters for improvement. The paper contributes toward developing a framework of assessment that provides guidance to measure sustainability at a microscale of a cluster and also at a scale of a city cumulatively, under each domain.

This study highlights the spatial patterns of high-tech clusters and the effects of high-technology (“high-tech”) industries on the urban economy in US Metropolitan Statistical Areas (MSAs) by employing a new Cluster Quotient index (CQ) and Seemingly Unrelated Regression model (SUR). The study finds that San Jose, CA and Washington, DC are the high-tech centers in the United States, and MSAs in California and Colorado play an important role in high-tech industries. After running the SUR model, the elasticity of the gross domestic product (GDP) is 0.15% for high-tech industries, and an increase of 1% of high-tech industries generates an increase of 0.29% in GDP at the 0.01 significance level. The findings of this article highlight that high-tech industries and the GDP interact with each other and have a positive two-way relationship. The results in this paper allow urban planners to develop policies to increase the number or proportion of high-tech industries for the economic growth of US MSAs.

The controversy over whether the path of prioritizing large cities sprawling or the path of prioritizing small cities development is better for Chinese urbanization is unresolved. In northeastern China, extremely low fertility and increasing rural emigration are weakening the population foundation for industrialization and urbanization. Therefore, the approach to urbanization is key to a regional economic revival. Survey data from 2014 on 1,242 migrant workers in 6 cities in Liaoning Province were used to analyze residential choices and their determinants to respond to the controversy. The results found that midsized or large cities and cities near the hometown were preferred over small cities and cities far from the hometown; therefore, prioritizing large cities sprawling is more responsive to migrant workers’ choices in northeastern China. Gender, age, educational attainment, wages, employment quality, income satisfaction, length of employment, urban health insurance, history of family migration, and family land size predicted the choices.

The connection between the built environment and the physical activity of people is increasingly emphasized in China, given its unique suburbanization and dramatic changes in lifestyle. This paper aims to provide more evidence on equivocal findings on specific built environments and physical activities by examining the roles of the built environment on people’s physical activity within suburban residences in Guangzhou (China). Multinomial logistic and ordinal regression analyses were used to identify the factors associated with physical activity that indicated the unique features of urban-type suburban residences: residential density, street connectivity, pedestrian infrastructure, design features, safety, destination accessibility, and pedestrian infrastructure. The confounding effects of individual sociodemographic characteristics are ascertained in interpretive, evaluative, and responsive transactions between the built environment and physical activity, highlighting the determinative nature of perceived environmental opportunities and barriers to physical activity. With the absence of operative transactions, key stakeholders of commodity housing developments should be motivated, and residents need to be educated and empowered to help realize a better, physically active living environment.

The urbanization process can have a profound impact on economic development, human society, natural resources, and the environment, and is closely related to sustainable development. As a developing country, China has experienced rapid urbanization that has brought forth not only economic development and income growth but also environmental degradation and an urban–rural income gap. To promote sustainable development during the urbanization process, it is necessary to assess the relative status of sustainable urbanization performance in the different regions of China and explore its driving forces. This study developed an indicator system against the background of China’s urbanization and adopted an improved entropy method to assess the social, economic, and environmental dimensions of urbanization performance in China at both the national and provincial levels. The results suggest that the national sustainable urbanization performance has improved greatly since 1990, in accordance with the increase in the urbanization rate. However, the environmental and social dimensions of urbanization performance lagged greatly behind that of the economic dimension. There was a large regional disparity among the different provinces in the 2000–2014 study period, with the highest aggregate sustainable urbanization levels concentrated in the eastern coastal region, in addition to the spatial disparity decreasing over the study period. Furthermore, the panel data regression analysis indicated that the market was the leading driving force for the different dimensions of sustainable urbanization in China, followed by intrinsic and administration forces. Finally, it is recommended that differentiated strategies should be pursued in different regions. Whereas western and central China mostly need to improve the developmental level of urban sustainability by providing more infrastructure, the eastern provinces require better coordination of the different dimensions of sustainable urbanization. This study not only may provide some policy implications for China to promote its sustainable urbanization but also may serve as a reference for other developing countries.

Walking, including access trips to public transport (PT), constitutes $\sim 60\%$ of commute trips in urban India. However, the quality of pedestrian infrastructure remains poor in Indian cities, leading to inconvenience and high risk to pedestrians. To assess this quality, pedestrian accessibility audits were conducted around 360 bus stops in Delhi. To ensure representativeness, bus stops were selected based on multicriteria stratified sampling, with the following three criteria: relative risk of pedestrian fatality, socioeconomic variables, and distance from city center. The Public Transport Accessibility (PTA) toolkit was used, which has a specific checklist of measurable definitions for rating the access indicators. PTA scores for pedestrian accessibility were predominantly low across Delhi. There was significant spatial clustering of the scores, indicating spatial disparity in the quality of pedestrian infrastructure, which was found to be in tandem with the spatial disparity of income levels. The authors advocate that this toolkit can be used effectively by city authorities and policymakers to undertake location- and indicator-specific improvements in pedestrian infrastructure around PT stops. This toolkit is pertinent for Indian cities, because virtual streetscape audit tools are not currently available.

From an academic perspective, compact land use and spatial development patterns are regarded as the primary aspects of urban development for environmental sustainability and government financing. However, whether these aspects concur with residents’ perceived quality of life is unclear. Because of differences in spatial structures, residents in sprawling and compact development areas differ in their perceptions and levels of satisfaction regarding quality of life. Identifying the characteristics of and differences among quality of life perceptions can facilitate the clarification of whether sustainable development and growth management fit the expectations of urban residents. This study examined the Taipei metropolitan area. In the survey, questionnaire copies were distributed to residents in sprawling and compact development areas. Structural equation modeling was applied to the collected data to explore the differences in residents’ perceptions of and satisfaction with quality of life. The study findings revealed that street space, commercial functions, neighborhood relationships, and household finances were four aspects exerting a significant effect on residents’ perceptions of and satisfaction with overall quality of life in sprawling development areas. Living space, commercial functions, neighborhood relationships, and household finances were significant factors influencing residents’ satisfaction with quality of life in compact development areas.

Pedestrianism is a key mode of transportation within an urban community. However, unlike motorized transport, pedestrians are not limited to using the codified infrastructure designed for foot travel (e.g., sidewalks). Pedestrians can reveal, in physical form, desired paths to connect origins and destinations. This exploratory study employed two methods to examine the extent and drivers of desired pedestrian paths and activity: (1) aerial photography and spatial analysis were used to create an inventory of desired paths on the campus of Florida State University, and (2) a survey of desired path users was administered to determine the drivers of this activity. A comparison of spatial data from 2013 and 2018 demonstrates an array of desired paths on campus and, over time, campus planners have codified many of these informal paths. The results from the survey demonstrate that pedestrians use desired paths primarily for efficiency but not at the expense of nighttime safety concerns. We offer desired paths as physical evidence of pedestrian preferences that planners can use to improve the design of pedestrian infrastructure.